Kyle Hernandez, Ph.D.

Research Assistant Professor, Department of Medicine, Section of Biomedical Data Science

Bioinformatics Manager, Center for Translational Data Science

kmhernan@uchicago.edu




 

Background

Dr. Hernandez has a diverse background that has centered on exploring the genetic architecture of complex traits, genotype-environment interactions (GxE), and large-scale bioinformatics approaches. His undergraduate work used odonates as a way to explore anthropogenic effects in the playa lakes of west Texas. For his Ph.D., he focused on evolutionary quantitative genetics, phenotypic plasticity, and invasive Bromus species. To better understand the utility of next-generation sequencing in exploring the genetic architecture of GxE, he worked as an NSF Postdoctoral Fellow at the University of Texas where he found his love of bioinformatics, complex genomes, and software engineering. Since 2013 Dr. Hernandez has been at the University of Chicago, first in the Center for Research Informatics as part of the bioinformatics core, then spending the majority of his effort working with CTDS on the NCI Genomic Data Commons (GDC) project. He then moved to an academic appointment that led to his current position as a Research Assistant Professor in the Department of Medicine, Section of Biomedical Data Science and Bioinformatics Manager in CTDS where he mentors a team of bioinformaticians and data scientists, serves as Co-PI of the VA Data Commons, and collaborates with other Faculty for research in the field of biomedical data science.

Research Interests

  • Bioinformatics cloud platforms and scaling of bioinformatics workflows

  • Genetic architecture of complex traits

  • AI/ML applications to automatic data curation and knowledge extraction

  • Improving “discoverability” (search) across multiple data domains, ontologies, and resources

  • Multi-omics integration

Education

  • B.S. - Biology - Texas Tech University

  • Ph.D. - Ecology, Evolution, and Population Biology - Purdue University

  • Postdoc - NSF Postdoctoral Fellowship - University of Texas at Austin

Positions

  • 2013-2019 Bioinformatician, Center for Research Informatics, University of Chicago, Chicago, IL.

  • 2017-2019 Research Assistant Professor, Department of Pediatrics, University of Chicago, Chicago, IL

  • 2020-present Bioinformatics Manager, Center for Translational Data Science

  • 2020-present Research Assistant Professor, Department of Medicine, University of Chicago, Chicago, IL

Honors

  • 2004-2005 Howard Hughes Medical Institute Undergraduate Research Scholar, Texas Tech University, Lubbock, TX

  • 2006-2009 Graduate Assistance in Areas of National Need Fellow, U.S. Department of Education, Purdue University, West Lafayette, IN

  • 2008-2010 Purdue Doctoral Fellowship, Purdue University, West Lafayette, IN

  • 2010 Certification in Applied Statistics, Purdue University, West Lafayette, IN

  • 2010 Certification in Applied Management Principles, Purdue University, West Lafayette, IN

Other Sites

PUblications

AI/ML Applications

  1. Kuang, X., Wang, F., Hernandez, K.M., Zhang, Z., and Grossman, R.L., 2022. Accurate and rapid prediction of tuberculosis drug resistance from genome sequence data using traditional machine learning algorithms and CNN. Scientific Reports, 12, 2427.

Biomedical Platforms and Large-scale Bioinformatics

  1. Bao, R.*, Hernandez, K.*, Huang, L., Kang, W., Bartom, E., Onel, K., Volchenboum, S., and J. Andrade. 2015. ExScalibur: A High-Performance Cloud-Enabled Suite for Whole Exome Germline and Somatic Mutation Identification. PloS One 10:e0135800. [*] Contributed equally to this work.

  2. Gao, G.F., Parker, J.S., Reynolds, S.M., Silva, T.C., Wang, L.B., Zhou, W., Akbani, R., Bailey, M., Balu, S., Berman, B.P., Brooks, D., Chen, H., Cherniak, A.D., Demchok, J.A., Ding, L., Felau, I., Gaheen, S., Gerhard, D.S., Heiman, D.I., Hernandez, K.M., Hoadley, K.A., Jayasinghe, R., Kemal, A., Knijnenburg, T.A., Lair, P.W., Mensa, M.K.A., Mungall, A.J., Robertson, A.G., Shen, H., Tarnuzzer, R., Wang, Z., Wyczalkowski, M., Yang, L., Zenklusen, J.C., Zhang, Z., The Genomic Data Analysis Network, Liang, H., and Noble, M.S., 2019. Before and After: Comparison of Legacy and Harmonized TCGA Genomic Data Commons’ Data. Cell Systems, 9(1), pp.24-34. 

  3. Zhang, Z., Hernandez, K., Savage, J., Li, S., Miller, D., Agrawal, S., Ortuno, F., Staud, L.M., Heath, A., and Grossman, R.L., 2021. Uniform genomic data analysis in the NCI Genomic Data Commons. Nature Communications, 12(1), pp.1-11.

  4. Heath, A.P., Ferretti, V., Agrawal, S., An, M., Angelakos, J.C., Arya, R., Bajari, R., Baqar, B., Barnowski, J.H.B, Burt, J., Catton, A., Chan, B.F., Chu, F., Cullion, K., Davidsen, T., Do, P., Dompierre, C., Ferguson, M.L., Fitzsimons, M.S., Ford, M., Fukuma, M., Gaheen, S., Ganji, G.L., Garcia, T.I., George, S.S., Gerhard, D.S., Gerthoffert, F., Gomez, F., Han, K., Hernandez, K.M., Issac, B., Jackson, R., Jensen, M.A., Joshi, S., Kadam, A., Khurana, A., Kim, K.M.J., Kraft, V.E., Li, S., Lichtenberg, T.M., Lodato, J., Lolla, L., Matrinov, P., Mazzone, J.A., Miller, D.P., Miller, I., Miller, J.S., Miyauchi, K., Murphy, M.W., Nullet, T., Ogwara, R.O., Ortuño, F.M., Pedrosa, J., Pham, P.L., Popov, M.Y., Porter, J.J., Powell, R., Rademacher, K., Reid, C.P., Rich, S., Rogel, B., Sahni, H., Savage, J.H., Schmitt, K.A., Simmons, T.J., Sislow, J., Spring, J., Stein, L., Sullivan, S., Tang, Y., Thiagarajan, M., Troyer, H.D., Wang, C., Wang, Z., West, B.L., Wilmer, A., Wilson, S., Wu, K., Wysocki, W.P., Xiang, L., Yamada, J.T., Yang, L., Yu, C., Yung, C.K., Zenklusen, J.C., Zhang, J., Zhang, Z., Zhao, Y., Zubair, A., Staudt, L.M., and Grossman, R.L., 2021. The NCI Genomic Data Commons. Nature Genetics, 53, pp.257-262.

  5. Barnes, C., Bajracharya, B., Cannalte, M., Gowani, Z., Haley, W., Kass-Hout, T., Hernandez, K., Ingram, M., Juvvala, H.P., Kuffel, G., Martinov, P., Maxwell, J.M., McCann, J., Malhotra, A., Metoki- Shlubsky, N., Meyer, C., Paredes, A., Qureshi, J., Ritter, X., Schumm, P., Shao, M., Sheth, U., Simmons, T., VanTol, A., Zhang, Z., and Grossman, R.L., 2022. The Biomedical Research Hub: a federated platform for patient research data. Journal of the American Medical Informatics Association, 29:4, pp619-625.

Cancer ‘Omics

  1. Singh, P., Brock, C.O., Volden, P.A., Hernandez, K., Skor, M., Kocherginsky, M, Park, J.E., Brady, M.J., and S.D. Conzen. 2015. Glucocorticoid receptor ChIP-sequencing of subcutaneous fat reveals modulation of inflammatory pathways. Obesity 23:2286-2293. http://onlinelibrary.wiley.com/doi/10.1002/oby.21251/full

  2. West, D.C., Pan, D., Tonsing-Carter, E.Y., Hernandez, K.M., Pierce, C.F., Styke, S.C., Bowie, K.R., Garcia, T.I., Kocherginsky, M., and S.D. Conzen. 2016. GR and ER co-activation alters the expression of differentiation genes and associates with improved ER+ breast cancer outcome. Molecular Cancer Research DOI: 10.1158/1541-7786.MCR-15-0433. http://mcr.aacrjournals.org/content/early/2016/04/30/1541-7786.MCR-15-0433

  3. Eckert, M.A., Pan, S., Hernandez, K.M., Loth, R.M., Andrade, J., Volchenboum, S.L., Faber, P., Montag, A., Lastra, R., Peter, M.E., Yamada, S.D., and E. Lengyel. 2016. Genomics of ovarian cancer progression reveals diverse metastatic trajectories including intraepithelial metastasis to the fallopian tube. Cancer Discovery doi:10.1158/2159-8290.CD-16-0607. http://cancerdiscovery.aacrjournals.org/content/early/2016/10/07/2159-8290.CD-16-0607

  4. Spranger, S., Luke, J.J., Bao, R., Zha, Y., Hernandez, K.M., Li, Y., Gajewski, A.P., Andrade, J. and Gajewski, T.F., 2016. Density of immunogenic antigens does not explain the presence or absence of the T-cell–inflamed tumor microenvironment in melanoma. Proceedings of the National Academy of Sciences, 113(48), pp.E7759-E7768.

  5. Applebaum, M.A., Jha, A.R., Kao, C., Hernandez, K.M., DeWane, G., Salwen, H.R., Chlenski, A., Dobratic, M., Mariani, C.J., Godley, L.A. and Prabhakar, N., 2016. Integrative genomics reveals hypoxia inducible genes that are associated with a poor prognosis in neuroblastoma patients. Oncotarget, 7(47), p.76816.

  6. Pekow, J., Hernandez, K., Meckel, K., Deng, Z., Haider, H.I., Khalil, A., Zhang, C., Talisila, N., Siva, S., Jasmine, F. and Li, Y.C., 2019. IBD-associated Colon Cancers Differ in DNA Methylation and Gene Expression Profiles Compared With Sporadic Colon Cancers. Journal of Crohn's and Colitis.

  7. Eckert, M.A., Coscia, F., Chryplewicz, A., Chang, J.W., Hernandez, K.M., Pan, S., Tienda, S.M., Nahotko, D.A., Li, G., Blaženović, I. and Lastra, R.R., 2019. Proteomics reveals NNMT as a master metabolic regulator of cancer-associated fibroblasts. Nature, 569(7758), p.723.

  8. Tonsing-Carter, E., Hernandez, K.M., Kim, C.R., Harkless, R.V., Oh, A., Bowie, K.R., West-Szymanski, D.C., Betancourt-Ponce, M.A., Green, B.D., Lastra, R.R. and Fleming, G.F., 2019. Glucocorticoid receptor modulation decreases ER-positive breast cancer cell proliferation and suppresses wild-type and mutant ER chromatin association. Breast Cancer Research, 21(1), p.82.

  9. Bao, R., Spranger, S., Hernandez, K., Zha, Y., Pytel, P., Luke, J.J., Gajewski, T.F., Volchenboum, S.L., Cohn, S.L., and Desai, A.V., 2021. Immunogenomic determinants of tumor microenvironment correlate with superior survival in high-risk neuroblastoma. Journal for ImmunoTherapy of Cancer, 9(7).

  10. Arnovitz, S., Mathur, P., Tracy, M., Mohsin, A., Mondal, S., Quandt, J., Hernandez, K.M., Khazaie, K., Dose, M., Emmanuel, A.O., and Gounari, F., 2022. Tcf-1 promotes genomic instability and T cell transformation in response to aberrant B-catenin activation. PNAS, 119:32, e2201493119.

Genetic Architecture and Evolutionary Genetics

  1. Lowry, D.B., Hernandez, K., Taylor, S.H., Meyer, E., Logan, T.L., Barry, K.W., Chapman, J.A., Rokhsar, D.S., Schmutz, J., and T.E. Juenger. 2014. The genetics of divergence and reproductive isolation between ecotypes of Panicum hallii. New Phytologist 205:402-414. http://onlinelibrary.wiley.com/doi/10.1111/nph.13027/full

  2. Malcom, J.W., Hernandez, K.M., Likos, R., Wayne, T., Leibold, M.A., and T.E. Juenger. 2014. Extensive cross-environment fitness variation lies along axes of genetic variation in the model alga, Chlamydomonas reinhardtii. New Phytologist 205:841-851. http://onlinelibrary.wiley.com/doi/10.1111/nph.13063/abstract 

  3. Des Marais, D.L., Razzaque, S., Hernandez, K.M., Garvin, D.F., and T.E. Juenger. 2016. Quantitative trait loci associated with natural diversity in water-use efficiency and response to soil drying in Brachypodium distachyon. Plant Science 251:2-11. http://www.sciencedirect.com/science/article/pii/S0168945216300425

  4. Weafer, J., Gray, J.C., Hernandez, K., Palmer, A.A., MacKillop, J. and de Wit, H., 2017. Hierarchical investigation of genetic influences on response inhibition in healthy young adults. Experimental and clinical psychopharmacology, 25(6), p.512.

  5. Gray, J.C., MacKillop, J., Weafer, J., Hernandez, K.M., Gao, J., Palmer, A.A. and de Wit, H., 2018. Genetic analysis of impulsive personality traits: Examination of a priori candidates and genome-wide variation. Psychiatry research, 259, pp.398-404.

Virology and Epidemiology

  1. Bao, R., Hernandez, K., Huang, L., and Luke, J.J., 2020. ACE2 and TMPRSS2 expression by clinical, HLA, immune, and microbial correlates across 34 human cancers and matched normal tissues: implications for SARS-CoV-2 COVID-19. Journal for ImmunoTherapy of Cancer, 8(2), doi:10.1136/jitc- 2020-001020.

  2. Sapoval, N., Mahmoud, M., Jochum, M., Liu, Y., Elworth, R.A.L., Wang, Q., Albin, D., Ogilvie, H., Lee, M.D., Villapol, S., Hernandez, K., Berry, I.M., Foox, J., Bheshti, A., Ternus, K., Aagaard, K., Posada, D., Mason, C., Sedlazeck, F.J., and Treangen, T.J., 2021. Hidden genomic diversity of SAR-CoV-2: implications for qRT-PCR diagnostics and transmission. Genome Research, doi: 10.1101/gr.268961.120.

  3. Saravia-Butler, A.M., Schisler, J.C., Taylor, D., Beheshti, A., Butler, D., Meydan, C., Foox, J., Hernandez, K., Mozsary, C., Mason, C.E., and Meller, R., 2022. Host transcriptional responses in nasal swabs identify potential SARS-CoV-2 infection in PCR negative patients. iScience, 25:11, 105310.

Other

  1. Hernandez, K.M., Reece, B.A., and N.E. McIntyre. 2006. Effects of anthropogenic land use on Odonata in playas of the Southern High Plains. Western North American Naturalist 66:273-238. http://www.bioone.org/doi/abs/10.3398/1527-0904(2006)66%5B273:EOALUO%5D2.0.CO%3B2

  2. McConnell, S.C., Hernandez, K.M., Wcisel, D.J., Kettleborough, R.N., Stemple, D.L., Yoder, J.A., Andrade, J., and J.L.O. de Jong. 2016. Alternative haplotypes of antigen processing genes in zebrafish diverged early in vertebrate evolution. PNAS 113: E5014-E5023. http://www.pnas.org/content/113/34/E5014.short

  3. Singh, U., Hernandez, K.M., Aronow, B.J., and Wurtele, E.S., 2021. African Americans and European Americans exhibit distinct gene expression patterns across tissues and tumors associated with immunologic functions and environmental exposures. Scientific Reports, 11, 9905.

  4. Wcisel, D.J., Dornburg, A., McConnell, S.C., Hernandez, K.M., Andrade, J., de Jong, J.L.O., Litman, G.W., and Yoder, J.A., 2022. A highly diverse set of novel immunoglobulin-like transcript (NILT) genes in zebrafish indicates a wide range of functions with complex relationships to mammalian receptors. Immunogenetics, doi:10.1007/s00251-022-01270-9.

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